## [practice of association rules in data mining] Intelligent Recommendation Algorithm of association rules

Data description
Data parameters OrderNumber: customer nickname LineNumber: purchase order. For example, the first three lines respectively represent three goods purchased by the same customer Model: trade name
Problem description
Application of intelligent algorithm recommendation of association rules based on shopping basket.
Three basic ...

Posted by **Skara** on *Sat, 04 Dec 2021 22:41:39 -0800*

## Experiment 8 project case - e-commerce data analysis

Level 1: Statistics of user churn
Task description
This task: according to the user behavior data, write MapReduce program to count the loss of users.
Relevant knowledge
This training is an intermediate difficulty MapReduce programming exercise, which simulates the statistical analysis of e-commerce data in real scenes. Therefore, it is ...

Posted by **kane007** on *Sat, 04 Dec 2021 19:59:57 -0800*

## Matlab uses BUGS Markov regime to transform Markov switching random volatility model, sequential Monte Carlo and M-H sampling to analyze time series data

Original link: http://tecdat.cn/?p=24498In this example, we consider Markov transformation stochastic volatility model.statistical modelGive Way Are dependent variables and Unobserved log volatility The stochastic volatility model is defined as follows Zone variable Following a two-state Markov ...

Posted by **msandersen** on *Thu, 02 Dec 2021 16:04:31 -0800*

## Machine learning algorithm

1. Time series algorithm
1.1 differential autoregressive moving average model (Arima)
1.1.1 overview
ARIMA is a typical time series model, which consists of three parts: AR model (autoregressive model) and MA model (moving average model), as well as the order I of difference. Therefore, ...

Posted by **chrbar** on *Tue, 30 Nov 2021 21:35:26 -0800*

## Pandas table beauty skills

Official account: Special HouseAuthor: PeterEditor: Peter
Hello, I'm Peter~
This article mainly introduces how to beautify the data of Pandas DataFrame. It is mainly realized through two methods in Pandas:
Styler.applymap: returns a single string with CSS attribute value pairs element by elementStyler.apply: returns Series or DataFrame wit ...

Posted by **john0117** on *Tue, 30 Nov 2021 07:01:12 -0800*

## Data analysis of hands-on learning -- establishment and evaluation of model

1. Model construction
1.1 get modeling data
#Read raw data
train = pd.read_csv('train.csv')
#Read cleaned data set
data = pd.read_csv('clear_data.csv')
1.2 select appropriate model
Before model selection, we need to know whether the data set is finally supervised learning or unsupervised learning
Machine learning is mainly divided into ...

Posted by **boon4376** on *Thu, 25 Nov 2021 10:27:37 -0800*

## Introduction to KMmeans clustering learning:

1, Introduction to KMeans algorithm:
K in the name of KMeans algorithm represents the number of categories, and Means represents the mean value of samples in each category. Therefore, KMeans algorithm is also called k-Means algorithm. KMeans algorithm takes distance as the measure of similarity between samples, and assigns samples with similar ...

Posted by **narimanam** on *Mon, 22 Nov 2021 21:35:54 -0800*

## Clustering algorithm KMeans

preface
Although the code is often very long, it is annotation for understanding
1, KMeans
KMeans can be said to be one of the simplest clustering algorithms
1.1 how does kmeans work
Key concepts: cluster and centroid
KMeans algorithm divides the characteristic matrix X of a group of N samples into K clusters without inters ...

Posted by **GrizzlyBear** on *Sun, 21 Nov 2021 01:26:34 -0800*

## [talking about python crawler 2] etree method based on lxml library combined with xpath method -- crawling the contents of the ranking list and generating the word cloud map of the ranking list

Hello, everyone. I'm a studious junior brother. Today, I will continue to explain the second method I wrote: etree method based on lxml library combined with xpath method - crawling the contents of the ranking list and generating the word cloud map.
The learning experience is mainly divided into three lectures:
...

Posted by **liquidchild_au** on *Fri, 19 Nov 2021 21:50:45 -0800*

## Wu Enda's programming assignment in the second week

Title Description
Given the training data set (pictures of cats), let's build a simple neural network to identify cats.
Dataset description
There are 209 pictures in the training set, and the shape of each picture is (64, 64, 3) There are 50 pictures in the test set, and the shape of each picture is (64, 64, 3) classes stores two string data ...

Posted by **HaXoRL33T** on *Fri, 19 Nov 2021 16:36:49 -0800*